/MetalGAN

Generative adverserial neural network for metal band logo generation

Primary LanguagePython

MetalGAN

Generative adverserial neural network for metal band logo generation

Overview

This project is a personal project to test my capabilities for implementing a GAN. I chose to try and generate metal band logos for several reasons.

  1. I personally favour metal music.
  2. I have abundunt data (~8k images). More would be better but I have found examples of impressive GANs trained on less than 1k images.
  3. The logo images represent a good distibution for a GAN:
  • they are mostly grey-scale (or monochrome and thus easily converted to grey-scale)
  • they retain meaning when resized
  • the can be quite hard to read, which makes the generator's job of creating believable images much easier

I am running most of the training on my personal computer, thus I have to keep to as little computing power as possible. The implementation is mostly based on stackGAN. currently this is a work in progress

Results

First results with 64x64 images were not too impressive, but they proved that I am on the right track. example

For the second version I added a higher definition block, and added progressive training of different layers. example Images are improving, but training is becoming much more time-expensive the higher the resolution.

What to expect

I am currently tring to add a character based encoder, so that the GAN will be able to create a logo for a given name.